This study demonstrates that deep learning algorithms, trained on a diverse international cohort of 1280 patients, can accurately detect COVID-19 pneumonia on chest CT scans. The algorithms achieved up to 90.8% accuracy, 84% sensitivity, and 93% specificity in an independent test set of 1337 patients. The study highlights the potential of AI to aid in rapid and accurate evaluation of CT scans for COVID-19.
Publisher
Nature Communications
Published On
Nov 16, 2020
Authors
Stephanie A Harmon, Thomas H Sanford, Sheng Xu, Evrim B Turkbey, Holger Roth, Ziyue Xu, Dong Yang, Andriy Myronenko, Victoria Anderson, Amel Amalu, Maxime Blain, Michael Kassin, Dilara Long, Nicole Varble, Stephanie M Walker, Ulas Baci, Anna Maria Ierardi, Elvira Stellato, Guido Giovanni Plensich, Giuseppe Franceschelli, Cristiano Girelloni, Giovanni Irmici, Dominic Labella, Dima Hammoud, Ashkan Malayeri, Elizabeth Jones, Ronald M Summers, Peter L Choyke, Daguang Xu, Mona Flores, Kaku Tamura, Hioriumi Obinata, Hitoshi Mori, Francesca Patella, Maurizio Caritati, Gianpaolo Carraieillo, Peng An, Bradford J Wood, Baris Turkbey
Tags
deep learning
COVID-19
CT scans
pneumonia detection
artificial intelligence
medical imaging
accuracy
Related Publications
Explore these studies to deepen your understanding of the subject.
